In the last few years, modern communication systems have witnessed a significant shift towards the use of mobile communication systems. Latest statistics show that the total number of mobile phones subscribers is about 5 billion by the end of 2014.
One of the main limitations that mobile users are currently facing is the power limitation of their devices, which usually rely on small size batteries. The power problem in wireless networks is mainly due to the severe nature of the wireless communications channels, which usually requires pumping additional transmission power.
In addition to the transmission power, the processing power is also becoming a dominant factor that determines the power efficiency of mobile devices. The processing power is required to extract the information at the receiver side which includes channel estimation, synchronization, error correction and data detection.
Generally speaking, the processing power consumed per information bit is not significant. Therefore, the total processing power for low data rate communications is tolerable in general. However, a significant portion of the traffic over mobile networks is currently carrying video information, which implies that the number of bits to be processed per unit time is huge. Consequently, the processing power becomes a dominant factor that determines the overall power consumption in the mobile handset.
Orthogonal Frequency Division Multiplexing (OFDM) is well known as a highly spectral efficient transmission scheme capable of dealing with severe channel impairment encountered in a wireless environment. The basic idea of OFDM is to divide the available spectrum into several sub-channels (sub-carriers). By making all sub-channels narrowband, they experience almost flat fading, which makes equalization very simple. To obtain a high spectral efficiency the frequency response of the sub-channels are overlapping and orthogonal. This orthogonality can be completely maintained, even though the signal passes through a time-dispersive channel, by introducing a cyclic prefix (or guard interval). A cyclic prefix is a copy of the last part of the OFDM symbol which is pre-appended to the transmitted symbol. This makes the transmitted signal periodic, which plays a decisive role in avoiding inter-symbol and inter-carrier interference.
OFDM signaling can largely eliminate the effects of inter-symbol interference for high-speed transmission in highly dispersive channels by separating a single high speed bit stream into a multiplicity of much lower speed bit streams each modulating a different sub-carrier.
Fortunately, the apparently very complex processes of modulating (and demodulating) thousands of sub-carriers simultaneously are equivalent to Discrete Fourier Transform operations, for which efficient Fast Fourier Transform (FFT) algorithms exist. Thus, integrated circuit implementations of OFDM demodulators are feasible for affordable mass-produced receivers. Furthermore, the use of error coding, interleaving, and channel-state information (CSI) allows OFDM signaling to function in a manner that is well suited to the needs of the terrestrial broadcasting channel.
To combat frequency-selective fading and interference, channel coding with soft-decision decoding can be properly integrated with an OFDM system. By means of interleaving the coded data before assigning them to OFDM sub-carriers at the modulator, clusters of errors caused by channel impairment can be broken up at the receiving end. The soft-decision decoding is carried out by a well known Viterbi decoder in an OFDM receiver. The Viterbi decoder is a sort of maximum likelihood decoder for the convolutional coding and must be fed with a soft decision comprising a measure or metric of the received signal. A metric can be made separately for each received bit to indicate a degree of confidence.
When data are modulated onto a single carrier in a time-invariant system, then a priori all data symbols suffer from the same noise power on average; the soft-decision information simply needs to take note of the random symbol-by-symbol variations that this noise causes. When data are modulated onto the multiple OFDM sub-carriers, the metrics become slightly more complicated as the various carriers will have different signal-to-noise ratios (SNR). For example, a carrier which falls into a notch in the frequency response will comprise mostly noise; one in the peak will suffer much less. Thus, in addition to the symbol-by-symbol variations, there is another factor to take account for in soft decisions: data conveyed by sub-carriers having a high SNR are a priori more reliable than those conveyed by sub-carriers having low SNR. This priori information is usually known as channel-state information (CSI). The CSI concept can be extended to embrace interference which affects sub-carriers selectively. The inclusion of CSI in the generation of soft decisions is the key to the unique performance of OFDM in the presence of frequency-selective fading and interference
One of the main advantages of OFDM is that each subcarrier experiences flat fading while the overall signal spectrum suffers from frequency-selective fading. Moreover, incorporating the concept of cyclic prefix (CP) prevents inter-symbol-interference (ISI) as long as the CP length is larger than the maximum delay of the channel. Consequently, low-complexity single-tap equalizers can be utilized to eliminate the impact of the multipath fading channel. Under such circumstances, the OFDM demodulation process can be performed once the fading parameters at each subcarrier channel state information (CSI), is known accurately. Towards this goal, robust channel estimation techniques should be invoked to avoid performance degradation.
Further, the issue of channel estimation has been considered extensively in the literature, the works reported in are just a few examples to mention. In general, channel estimation can be classified into blind, and pilot-aided techniques. Blind estimation techniques are spectrally efficient because they do not require any overhead to estimate the CSI. Nevertheless, such techniques have not been incorporated in practical OFDM systems yet. Pilot-based CSI estimation is preferred for practical systems because usually it is more robust and less complex. In pilot based CSI estimation, the pilot symbols are embedded within the subcarriers of the transmitted OFDM signal in time and frequency domain, hence the pilots form a two dimensional (2-D) grid. The density of the pilot symbols depends on the frequency-selectivity and time variation of the channel, or equivalently, the coherence bandwidth and coherence time of the channel. The channel response at the pilot symbols can be easily obtained using least square frequency domain estimation, the channel parameters at other subcarriers can be obtained using various interpolation techniques.
The density of the pilot grid and the interpolation technique used create a compromise between the error performance, spectral efficiency and the computational complexity. The spectral efficiency is determined by the grid density which has to satisfy the 2-D sampling theorem. The computational complexity is determined by the interpolation technique used, optimal interpolation requires a 2-D Wiener filter that exploits the time and frequency correlation of the channel, however it is substantially complex to implement. In time-varying channels, the spectral efficiency can be enhanced by changing the pilots' grid structure adaptively based on the channel conditions. The complexity can be reduced by decomposing the 2-D interpolation process into two cascaded 1-D processes, and then use less computationally involved interpolation schemes.
However, low complexity interpolation is usually accompanied with error performance degradation. It is also worth noting that most practical OFDM based systems utilize fixed grid pattern structure. Once the channel parameters are obtained for data subcarriers, the received samples at the output of the fast Fourier transform (FFT) are equalized to compensate for the channel fading. Fortunately, the equalization for OFDM is performed in frequency domain using single tap equalizers. The equalizer outputs, which are denoted as the decision variables, will be applied to a maximum likelihood detector (MLD) to regenerate the information symbols.